Methods: An observational study was conducted among 3935 patients presenting with acute upper respiratory illnesses in the ambulatory settings between 2012 and 2014.
Results: The VP4/VP2 gene was genotyped from all 976 RV-positive specimens, where the predominance of RV-A (49%) was observed, followed by RV-C (38%) and RV-B (13%). A significant regression in median nasopharyngeal viral load (VL) (P < .001) was observed, from 883 viral copies/µL at 1-2 days after symptom onset to 312 viral copies/µL at 3-4 days and 158 viral copies/µL at 5-7 days, before declining to 35 viral copies/µL at ≥8 days. In comparison with RV-A (median VL, 217 copies/µL) and RV-B (median VL, 275 copies/µL), RV-C-infected subjects produced higher VL (505 copies/µL; P < .001). Importantly, higher RV VL (median, 348 copies/µL) was associated with more severe respiratory symptoms (Total Symptom Severity Score ≥17, P = .017). A total of 83 phylogenetic-based transmission clusters were identified in the population. It was observed that the relative humidity was the strongest environmental predictor of RV seasonality in the tropical climate.
Conclusions: Our findings underline the role of VL in increasing disease severity attributed to RV-C infection, and unravel the factors that fuel the population transmission dynamics of RV.
METHODS: This study used data from the Global COVID-19 Index provided by PEMANDU Associates. The sample, representing 161 countries, comprised the number of confirmed cases, deaths, stringency indices, population density and GNI per capita (USD). Correlation matrices were computed to reveal the association between the variables at three time points: day-30, day-60 and day-90. Three separate principal component analyses were computed for similar time points, and several standardized plots were produced.
RESULTS: Confirmed cases and deaths due to COVID-19 showed positive but weak correlation with stringency and GNI per capita. Through principal component analysis, the first two principal components captured close to 70% of the variance of the data. The first component can be viewed as the severity of the COVID-19 surge in countries, whereas the second component largely corresponded to population density, followed by GNI per capita of countries. Multivariate visualization of the two dominating principal components provided a standardized comparison of the situation in the161 countries, performed on day-30, day-60 and day-90 since the first confirmed cases in countries worldwide.
CONCLUSION: Visualization of the global spread of COVID-19 showed the unequal severity of the pandemic across continents and over time. Distinct patterns in clusters of countries, which separated many European countries from those in Africa, suggested a contrast in terms of stringency measures and wealth of a country. The African continent appeared to fare better in terms of the COVID-19 pandemic and the burden of mortality in the first 90 days. A noticeable worsening trend was observed in several countries in the same relative time frame of the disease's first 90 days, especially in the United States of America.
METHODS: A molecular epidemiological investigation of CVA21 was conducted among patients presenting with acute upper respiratory illnesses in the ambulatory settings between 2012 and 2014 in Kuala Lumpur, Malaysia.
RESULTS: Epidemiological surveillance of acute respiratory infections (n = 3935) showed low-level detection of CVA21 (0.08%, 1.4 cases/year) in Kuala Lumpur, with no clear seasonal distribution. Phylogenetic analysis of the new complete genomes showed close relationship with CVA21 strains from China and the United States. Spatio-temporal mapping of the VP1 gene determined 2 major clusters circulating worldwide, with inter-country lineage migration and strain replacement occurring over time.
CONCLUSIONS: The study highlights the emerging role of CVA21 in causing sporadic acute respiratory outbreaks.
METHODS AND RESULTS: Autophagy level in the HCC patient-derived cancer and non-cancer tissues was determined by immunohistochemistry (IHC) targeting SQSTM1, LC3A and LC3B proteins. Significance tests of clinicopathological variables were tested using the Fisher's exact or Chi-square tests. Gene and miRNA expression assays were carried out and analyzed using Nanostring platform and software followed by validation of other online bioinformatics tools, namely String and miRabel. Autophagy expression was significantly higher in cancerous tissues compared to adjacent non-cancer tissues. High LC3B expression was associated with advanced tumor histology grade and tumor location. Nanostring gene expression analysis revealed that SQSTM1, PARP1 and ATG9A genes were upregulated in HCC tissues compared to non-cancer tissues while SIRT1 gene was downregulated. These genes are closely related to an autophagy pathway in HCC. Further, using miRabel tool, three downregulated miRNAs (hsa-miR-16b-5p, hsa-miR-34a-5p, and hsa-miR-660-5p) and one upregulated miRNA (hsa-miR-539-5p) were found to closely interact with the abovementioned autophagy-related genes. We then mapped out the possible pathway involving the genes and miRNAs in HCC tissues.
CONCLUSIONS: We conclude that autophagy events are more active in HCC tissues compared to the adjacent non-cancer tissues. We also reported the possible role of several miRNAs in regulating autophagy-related genes in the autophagy pathway in HCC. This may contribute to the development of potential therapeutic targets for improving HCC therapy. Future investigations are warranted to validate the target genes reported in this study using a larger sample size and more targeted molecular technique.